[1] "deleted rule no:"
[1] "3"
[1] "6"
function(rule, data)
{
	# qLS
	ct = contingencyTable(rule, data)
	return ((ct[["nrc"]]/ct[["nc"]])/(ct[["nr_c"]]/ct[["n_c"]]))
}
       3        6        8        9        1        2        4        5        7 
18.00000 18.00000 23.31429 65.82857      Inf      Inf      Inf      Inf      Inf 
$`1`
$`1`$class
[1] "Iris-setosa"

$`1`$condition
$`1`$condition[[1]]
[1] "petal_lgth" "< "         "2.45"      



$`2`
$`2`$class
[1] "Iris-versicolor"

$`2`$condition
$`2`$condition[[1]]
[1] "petal_lgth" ">="         "2.45"      

$`2`$condition[[2]]
[1] "petal_lgth" "< "         "4.75"      



$`3`
$`3`$class
[1] "Iris-setosa"

$`3`$condition
$`3`$condition[[1]]
[1] "petal_lgth" "< "         "2.35"      



$`4`
$`4`$class
[1] "Iris-versicolor"

$`4`$condition
$`4`$condition[[1]]
[1] "petal_lgth" ">="         "2.35"      

$`4`$condition[[2]]
[1] "petal_lgth" "< "         "4.8"       



$`5`
$`5`$class
[1] "Iris-setosa"

$`5`$condition
$`5`$condition[[1]]
[1] "petal_wdth" "< "         "1.7"       

$`5`$condition[[2]]
[1] "petal_lgth" "< "         "2.6"       



$`6`
$`6`$class
[1] "Iris-versicolor"

$`6`$condition
$`6`$condition[[1]]
[1] "petal_wdth" "< "         "1.7"       

$`6`$condition[[2]]
[1] "petal_lgth" ">="         "2.6"       



$`7`
$`7`$class
[1] "Iris-virginica"

$`7`$condition
$`7`$condition[[1]]
[1] "petal_wdth" ">="         "1.7"       



[1] "iris predictResults[[2]]"
   Iris-setosa Iris-versicolor Iris-virginica
1            1       0.0000000      0.0000000
2            1       0.0000000      0.0000000
3            1       0.0000000      0.0000000
4            1       0.0000000      0.0000000
5            1       0.0000000      0.0000000
6            1       0.0000000      0.0000000
7            1       0.0000000      0.0000000
8            1       0.0000000      0.0000000
9            1       0.0000000      0.0000000
10           1       0.0000000      0.0000000
11           1       0.0000000      0.0000000
12           1       0.0000000      0.0000000
13           1       0.0000000      0.0000000
14           0       1.0000000      0.0000000
15           0       1.0000000      0.0000000
16           0       1.0000000      0.0000000
17           0       1.0000000      0.0000000
18           0       1.0000000      0.0000000
19           0       1.0000000      0.0000000
20           0       0.0000000      1.0000000
21           0       1.0000000      0.0000000
22           0       1.0000000      0.0000000
23           0       1.0000000      0.0000000
24           0       1.0000000      0.0000000
25           0       1.0000000      0.0000000
26           0       1.0000000      0.0000000
27           0       1.0000000      0.0000000
28           0       1.0000000      0.0000000
29           0       0.0000000      1.0000000
30           0       0.0000000      1.0000000
31           0       0.6666667      0.3333333
32           0       0.0000000      1.0000000
33           0       0.0000000      1.0000000
34           0       0.0000000      1.0000000
35           0       0.0000000      1.0000000
36           0       0.0000000      1.0000000
37           0       0.0000000      1.0000000
38           0       1.0000000      0.0000000
39           0       0.0000000      1.0000000
40           0       0.0000000      1.0000000
41           0       0.0000000      1.0000000
42           0       0.0000000      1.0000000
43           0       0.0000000      1.0000000
[1] "iris predictResultsQuality[[2]]"
[1] 40.33333
